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MarketsandMarkets forecasts the global artificial intelligence (AI) market size to grow USD 58.3 billion in 2021 to USD 309.6 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 39.7% during the forecast period. Various factors such as growth of data-based AI and advancement in deep learning and need to achieve robotic autonomy to stay competitive in a global market are expected to drive the adoption of the AI solutions and services. 

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COVID-19 impact on global AI market

The COVID-19 pandemic has encouraged new applications and technological developments within the sector. It has accelerated the adoption of AI in sectors such as healthcare. AI-based tools and solutions are being deployed at scale for responding to the crisis. Technology giants such as Microsoft, Google, Apple, Amazon, and Facebook are taking initiatives related to remote communications between patients and clinicians, contact tracing, and drug development. During the pandemic, various companies experienced significant increase in pressure from customers, while their number of available employees decreased. Various contact centers were unable to cope with demand or closed because of lockdown restrictions, leading to long delays in customer service queries, which dramatically affected the customer experience. Hence, the demand for conversational AI has been increasing to the forefront of technology enablers. Besides the healthcare sector, AI has been revolutionizing various industries to uphold business resilience. The education sector started using AI, while even online education start-ups began to offer personalized services in line with the needs and specific requirements of the students. The COVID-19 crisis has reinforced the need to transform the conventional education system into one driven by technology. Apart from changing the learning methodology, AI-powered machines also enabled educators in several ways, such as tracking student performances, identifying gaps in teaching techniques, and automating mundane administrative tasks.

Market Dynamics

Driver: Need to achieve robotic autonomy to stay competitive in a global market

Today, AI, including computer vision and ML, is changing the landscape of the robotics industry. To stay ahead in a global market, businesses have started considering fully autonomous robots that can perceive, interact, and conceptualize the world around them. As industries begin to navigate this modern technological revolution, they have started looking for trusted and experienced technology partners. Deep learning models use artificial neural nets for processing large quantities of data, including images, texts, and sounds, for producing accurate results. AI-driven automation has proven useful in various applications across numerous industries, including the aviation, medical, agriculture, energy, and material handling markets. AI is being used not only to automate tasks but also to diagnose equipment malfunctions or detect product anomalies. For instance, within the aviation industry, AI and ML can be used to predict peak travel times, assist with passenger check-in, and automate routine maintenance tasks. AI is being used across the board to automate dangerous tasks, augment or replace skilled labor, and streamline operations. And yet, despite these advances, AI still cannot think abstractly or creatively. This means that there is a need for an ever-evolving workforce that is trained in robotics and advanced manufacturing.

Restraint: Limited number of AI experts

AI is a complex system, and for developing, managing, and implementing AI systems, companies require workforce with certain skill sets. For instance, workforce dealing with AI systems should be aware of technologies such as cognitive computing, ML and machine intelligence, deep learning, and image recognition. The integration of AI solutions with the existing systems is a difficult task, which requires extensive data processing to replicate the behavior of a human brain. Even minor errors can result in system failure or malfunctioning of a certain solution, and this can drastically affect outcomes and desired results.

Professional services of a data scientist or a developer are needed to customize an existing ML-enabled AI service. As AI technology is still in the early stage of its life cycle, the workforce with in-depth knowledge of this technology is limited. Thus, the impact of this restraining factor is expected to remain high during the initial years of the forecast period.

Opportunity: Increase in government initiatives and growth in investments to leverage the AI technology

The growing applications and easy deployment modes have dragged governments’ attention toward the AI technology, which has led to the growing investments by governments in AI and its related technologies. Government authorities, public sector organizations, and NGOs have started allocating the budget for AI-based pilot programs for numerous AI applications, including road and public safety, traffic management, and digitization of government documents. In August 2020, the US government announced more than USD 1 billion to establish research labs for AI and quantum information science. Similarly, in 2017, the Chinese government announced the initiative named ‘lead the world in AI by 2030.’ The initiative works toward AI development and deployment in every sector. Additionally, China has won more than 900 patents related to facial recognition. In March 2021, the Government of Canada announced USD 518 million to develop research infrastructure for advanced technologies, wherein the UK government has invested USD 27.5 million to conduct 15 innovative AI research projects in the healthcare sector. Apart from this, Singapore’s Armed Forces (SAF) has been investing in AI to build an unmanned system to battle alongside its worriers. The Indian government’s NITI Aayog program, #AIforAll, is increasingly working toward augmenting the economic growth expected to reach 1.3% by 2035 with the help of AI technology.

Challenge: Data security and privacy concerns

Security threats would grow even further in the future. In the last four years, the financial impact of cybercrimes has increased by nearly 78%, and the time it takes to resolve cyberattacks has doubled. The increase in data from various sources is cumbersome for several IT teams. The inefficiency of managing exabytes and petabytes of data has increased chances of security breaches and data losses. In today’s competitive marketplace, marketing teams require real-time and secure data to deliver an outstanding customer experience. Organizations are gathering data through multiple touchpoints and virtually measuring it. Such data, which is used in support and communication, may include a variety of data types. These data types include public information, big data, and small data collected from customers. This data can include permissions, individual preferences, and updated contact information on products, services, and communication platforms. Thus, vendors need to ensure high-level data security to maintain customer trust. Cyberattacks have increased significantly and have become sophisticated. For instance, in recent times, cybercriminals have widespread tools to obtain anything from passwords to secret questions and token-generated passwords. In such situations, marketing and IT teams need to work concurrently, providing each other with insights on when and how the data is gathered, processed, and used in operations. Before buying data, organizations should do their research and ensure they are receiving data from a reputable provider offering accurate data. As the data consists of customer demographic information, organizations may develop algorithms that penalize individuals based on their age, gender, or ethnicity. Companies should always have a detailed and precise representation of customers, account for biases, and offer fairness.

The cloud segment to grow at a higher CAGR during the forecast period

The cloud segment is expected to account for higher CAGR during the forecast period. The cloud deployment mode provides multiple benefits, such as reduced operational costs, hassle-free deployment, and high scalability. Cloud deployment for NLP and ML tools in AI is expected to grow with the increasing awareness related to the benefits of cloud-based solutions contributinf to its growth in the market.

Marketing and sales segment to account for largest market size during the forecast period

The global AI market by business function is segmented into finance, security, HR, marketing and sales, and law. AI in the field of marketing is one of the largest and major applications, for media and advertising purposes. AI offers incredible profit opportunities for companies as programmatic advertising can result in high conversion opportunity by extending audience pools and reaching accurate targets with fine-tuned messaging leading to its adoption for marketing and sales.

APAC to account for higher CAGR during the forecast period

The AI market is segmented into five geographic regions: North America, Europe, APAC, MEA, and Latin America. Among these regions, North America is projected to hold the largest market share during the forecast period. The market in APAC is anticipated to grow at the highest CAGR during the forecast period. This growth can be attributed to the adoption of AI services in end-user industries, such as manufacturing, healthcare, and automotive in countries such as Japan, China, Australia, and South Korea.

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Key Market Players

Scope of the Report

This research report categorizes the artificial intelligence market based on offering, technology, business function, deployment mode, organization size, vertical, and regions.

By Offering:

• Hardware
  • Processor
  • Memory
  • Network
• Software
  • Application Program Interface (API)
  • Machine Learning Framework
• Services
  • Deployment and Integration
  • Support and Maintenance

By Technology:

• Machine Learning
  • Deep Learning
  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
  • Other Technology
• Natural Language Processing
• Context-Aware Computing
• Computer Vision

By Business Function:

• Marketing and Sales
• Security
• Finance
• Law
• Human Resource
• Other Business Function ()

By Deployment Mode:

• Cloud
• On-premises

By Organization Size:

• Large enterprises
• Small and medium-sized enterprises (SMEs)

By Vertical:

• BFSI
• Retail and eCommerce
• Telecommunication and IT
• Healthcare and Life Sciences
• Automotive
• Government and Defense
• Manufacturing
• Energy and Utilities
• Other Verticals (education, media and entertainment and travel and hospitality)

By Region:

• North America
  • US
  • Canada
• Europe
  • UK
  • Germany
  • France
  • Italy
  • Spain
  • Rest of Europe                 
• APAC
  • China
  • Japan
  • South Korea
  • India
  • Rest of APAC
• Middle East and Africa
  • Kingdom of Saudi Arabia
  • United Arab Emirates
  • South Africa
  • Rest of Middle East and Africa
• Latin America
  • Brazil
  • Mexico
  • Rest of Latin America

Recent Developments:

• In January 2021, Google launched Product Discovery Solutions for retail industry.  This suite would enhance the retailer’s eCommerce capabilities and help them provide enhance customer experience. Product Discovery Solutions for Retail brings together AI algorithms and a search service, Cloud Search for Retail, which leverages Google Search technology to power retailers’ product-finding tools.
• In November 2020, Microsoft announced the availability of Dynamic 365 Project Operations solution across India. The solution focuses on providing help to businesses in unifying operational workflows to provide visibility, collaboration, and insights to drive success across teams, from prospects to payments to profit. The solution is built on Microsoft Power Platform and uses real-time analytics to connect and empower leadership, sales, resourcing, project management, and accounting teams with the visibility needed to deliver services to customers on-time and on-budget..
• In December 2020, IBM enhanced the capabilities of Watson to help businesses scale the use of AI. The new capabilities of the Watson are designed to improve the automation of AI and enhance the precision of AI prediction. IBM Discovery will provide more precise answers to the client queries with the help of NLP.
• In April 2019, AWS enhanced AI services for NLP, speech-to-text transcription, and image detection. AWS added new features to its AI services, such as Amazon Comprehend. The new features allow users to process texts in the encrypted format as well. Customers are leveraging the new features of Amazon Comprehend.
• In September 2020, Facebook AI launched Dynabench, a Dynamic Benchmarking ML platform. The company launched a new research platform for data collection and benchmarking. Dynabench uses a dynamic adversarial data collection procedure to improve current benchmarking practices.
• In June 2020, Salesforce launched a new solution Einstein recommendation for Trailhead. The company brought AI capabilities in its online learning platform by launching Einstein recommendation. The new solution would create personalized, intelligent learning experience by guiding learners throughout their journeys. It also would provide recommendations on the basis of other similar learner’s preferences.
• In December 2020, Cisco announced the launch of a new Webex solution to deliver highly personalized insights and actionable recommendations to individuals and teams. Webex enables organizations to collaborate seamlessly and transform their employee and customer experiences. Webex is helping employees innovate and remain productive wherever they are. Since the pandemic, Webex has not only continued to help businesses thrive, it has also been an integral platform for governments to continue to lead remotely, doctors to meet with patients safely, and educators to teach students at a distance.